Title: Simultaneous structure discovery and parameter estimation in gene networks using a multi-objective GP-PSO hybrid approach
Authors: Xinye Cai, Praveen Koduru, Sanjoy Das, Stephen M. Welch
Addresses: Department of Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66502, USA. ' Department of Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66502, USA. ' Department of Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66502, USA. ' Agronomy Department, Kansas State University, Manhattan, KS 66502, USA
Abstract: This paper presents a hybrid algorithm based on Genetic Programming (GP) and Particle Swarm Optimisation (PSO) for the automated recovery of gene network structure. It uses gene expression time series data as well as phenotypic data pertaining to plant flowering time as its input data. The algorithm then attempts to discover simple structures to approximate the plant gene regulatory networks that produce model gene expressions and flowering times that closely resemble the input data. To show the efficacy of the proposed approach, simulation results applied to flowering time control in Arabidopsis thaliana are demonstrated and discussed.
Keywords: gene regulatory networks; genetic programming; PSO; particle swarm optimisation; multi-objective optimisation; bioinformatics; structure discovery; parameter estimation; gene networks; plant genes; plant flowering times; gene expressions.
DOI: 10.1504/IJBRA.2009.026418
International Journal of Bioinformatics Research and Applications, 2009 Vol.5 No.3, pp.254 - 268
Published online: 11 Jun 2009 *
Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article